scholarly journals A Study of the Socioeconomic Factors Influencing Migration in Russia

2019 ◽  
Vol 11 (6) ◽  
pp. 1650 ◽  
Author(s):  
Li Wang ◽  
Jixia Huang ◽  
Hongyan Cai ◽  
Hengzi Liu ◽  
Jinmei Lu ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Socioeconomic Factors ◽  
Fixed Effects ◽  
Economic Status ◽  
Population Decline ◽  
Spillover Effect ◽  
Net Migration ◽  
Far North ◽  
Per Capita ◽  
Regional Product

Russia has experienced population decline in years and the economic development in Russia is largely restricted by labor shortage, particularly for the Far North and East region. In order to explore the migration mechanisms, six socioeconomic factors were selected to explore the influences on the net migration. Data from the 82 regions covering four time periods (2000, 2005, 2010 and 2015) was processed use spatial panel econometric analysis and the time-period fixed effects Spatial Durbin Model (SDM) was selected as the best fit model after tests. The results indicates that, unemployment and infant death rate are significantly negatively associated with net migration, while urbanization rate, urban scale and life expectancy are significantly positively associated with net migration; every 100 USD increase in per capita GRP (Gross Regional Product) is positively related with averagely 5.4 net migrates in the region; every 1 year increase in life expectancy would increase 1052 net migrates; every 1sqm increase in urban scale would increase the net migrates by 11.75 and every 1% increase in unemployment would lead to a decrease of 0.54 net migrates. Spillover effect was also found for per capita GRP and life expectancy, indicating that the increase of per capita GRP and life expectancy in neighboring regions can also increase the attractiveness in one region. It can be concluded that better job market, better economic status and health related wellbeing are all attracting factors for migrates and these factors can even make the neighborhood region more attractive for immigrates. Considering the ambitious development plan for the Russia Far North and East regions, related suggestions on attracting migrates are provided.

scholarly journals Analysis of Determinant of Life Expectancy in East Java Province

2019 ◽  
Vol 8 (1) ◽  
pp. 30-41
Author(s):  
Nurnas Kavila Elnung ◽  
Yozi Aulia Rahman
Keyword(s):  
Life Expectancy ◽  
Research Methods ◽  
Fixed Effects ◽  
Revenue Sharing ◽  
Fixed Effects Model ◽  
Tobacco Products ◽  
Quantitative Research Methods ◽  
Improve Life Expectancy ◽  
Per Capita ◽  
The Impact

Economic development in East Java Province increases each year, can be seen from the Gross Regional Domestic Product (GRDP) Per Capita is increasing. The increase in GRDP Per Capita, cigarette consumption can increase so that the impact on tax receipts and an increase in life expectancy is low. Tax receipts made as the Province of East Java with revenue sharing fund of tobacco products excise highest. The purpose of this study was to analyze the influence of revenue sharing fund of tobacco products excise, betel leaves and tobacco expenditures and GRDP Per capita against life expectancy in East Java Province. Research methods used in this research is quantitative research methods with processing and data analysis technique used is Panel regression analysis with Fixed Effects Model (FEM). The results showed that only the GRDP Per Capita  affects life expectancy while revenue sharing fund of tobacco products excise and expenditure of tobacco and betel leaves don't effect on life expectancy in East Java province. Based on those results, so in an attempt to improve life expectancy in East Java province by improving the use of programme revenue sharing fund of tobacco products excise that can provide direct benefits to society such as examination health routine.

scholarly journals Spatiotemporal distribution and sociodemographic and socioeconomic factors associated with primary and secondary syphilis in Guangdong, China, 2005–2017

2021 ◽  
Vol 15 (8) ◽  
pp. e0009621
Author(s):  
Shangqing Tang ◽  
Lishuo Shi ◽  
Wen Chen ◽  
Peizhen Zhao ◽  
Heping Zheng ◽  
...  
Keyword(s):  
Population Density ◽  
Gross Domestic Product ◽  
Socioeconomic Factors ◽  
Migration Rate ◽  
Secondary Syphilis ◽  
Spatial Effects ◽  
Factors Associated ◽  
Net Migration ◽  
Per Capita ◽  
Health Institutions

Background Previous studies exploring the factors associated with the incidence of syphilis have mostly focused on individual-level factors. However, recent evidence has indicated that social-level factors, such as sociodemographic and socioeconomic factors, also affect the incidence of syphilis. Studies on the sociodemographic and socioeconomic factors associated with syphilis incidence are scarce, and they have rarely controlled for spatial effects, even though syphilis shows spatial autocorrelation. Methodology/Principal findings Syphilis data from 21 cities in Guangdong province between 2005 and 2017 were provided by the National Notifiable Infectious Disease Reporting Information System. The incidence time series, incidence map, and space-time scanning data were used to visualize the spatiotemporal distribution. The spatial panel data model was then applied to explore the relationship between sociodemographic factors (population density, net migration rate, male:female ratio, and the number of health institutions per 1,000 residents), socioeconomic factors (gross domestic product per capita, the proportion of secondary/tertiary industry), and the incidence of primary and secondary syphilis after controlling for spatial effects. The incidence of syphilis increased slowly from 2005 (11.91 per 100,000) to 2011 (13.42 per 100,000) and then began to decrease, reaching 6.55 per 100,000 in 2017. High-risk clusters of syphilis tended to shift from developed areas to underdeveloped areas. An inverted U-shaped relationship was found between syphilis incidence and gross domestic product per capita. Moreover, syphilis incidence was significantly associated with population density (β = 2.844, P = 0.006), the number of health institutions per 1,000 residents (β = -0.095, P = 0.007), and the net migration rate (β = -0.219, P = 0.002). Conclusions/Significance Our findings suggest that the incidence of primary and secondary syphilis first increase before decreasing as economic development increases further. These results emphasize the necessity to prevent syphilis in regions at the early stages of economic growth.

scholarly journals Decentralization and Its Impact on Growth in India

2021 ◽  
Vol 16 (1) ◽  
pp. 130-151
Author(s):  
Fernanda Andrade de Xavier ◽  
Aparna P. Lolayekar ◽  
Pranab Mukhopadhyay
Keyword(s):  
Economic Growth ◽  
Capita Income ◽  
Fixed Effects ◽  
Capital Expenditure ◽  
Per Capita Income ◽  
Reverse Causality ◽  
Social Expenditure ◽  
Causality Test ◽  
Per Capita ◽  
National Growth

We study the effect of revenue decentralization (RD) and expenditure decentralization (ED) on sub-national growth in India from 1981–1982 to 2015–2016 for 14 large (non-special-category) states. Our study provides evidence that both RD and ED play a defining role in India’s sub-national growth in this three-and-a-half-decade period. We use a panel data model with fixed effects (FE) and Driscoll and Kraay standard errors that control for heteroscedasticity, autocorrelation and cross-sectional dependence. To test for causality between growth and decentralization, we use the Granger non-causality test. The regression analysis is supplemented with the distribution dynamics approach. We find that: (a) While decentralization Granger-caused economic growth, the reverse causality effect of growth on decentralization was not significant; (b) Economic growth increased significantly after liberalization; (c) Decentralization, capital expenditure and social expenditure had significant positive impacts on economic growth; and (d) States that had high levels of decentralization also had high levels of per capita income, while states that had low decentralization also exhibited low per capita income.

scholarly journals COVID-19 Mortality Rate and Its Incidence in Latin America: Dependence on Demographic and Economic Variables

2021 ◽  
Vol 18 (13) ◽  
pp. 6900
Author(s):  
Javier Cifuentes-Faura
Keyword(s):  
Latin America ◽  
Mortality Rate ◽  
Population Density ◽  
Life Expectancy ◽  
Latin American ◽  
Positive Influence ◽  
Death Rates ◽  
Per Capita ◽  
Latin American Countries ◽  
Quality Infrastructure

The pandemic caused by COVID-19 has left millions infected and dead around the world, with Latin America being one of the most affected areas. In this work, we have sought to determine, by means of a multiple regression analysis and a study of correlations, the influence of population density, life expectancy, and proportion of the population in vulnerable employment, together with GDP per capita, on the mortality rate due to COVID-19 in Latin American countries. The results indicated that countries with higher population density had lower numbers of deaths. Population in vulnerable employment and GDP showed a positive influence, while life expectancy did not appear to significantly affect the number of COVID-19 deaths. In addition, the influence of these variables on the number of confirmed cases of COVID-19 was analyzed. It can be concluded that the lack of resources can be a major burden for the vulnerable population in combating COVID-19 and that population density can ensure better designed institutions and quality infrastructure to achieve social distancing and, together with effective measures, lower death rates.

scholarly journals Drivers of CO2-Emissions in Fossil Fuel Abundant Settings: (Pooled) Mean Group and Nonparametric Panel Analyses

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3956 ◽  
Author(s):  
Elkhan Richard Sadik-Zada ◽  
Wilhelm Loewenstein
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Environmental Kuznets Curve ◽  
Fixed Effects ◽  
Fossil Fuel ◽  
Substantial Reduction ◽  
Resource Curse ◽  
Time Interval ◽  
Kuznets Curve ◽  
Per Capita

The present inquiry addresses the income-environment relationship in oil-producing countries and scrutinizes the further drivers of atmospheric pollution in the respective settings. The existing literature that tests the environmental Kuznets curve hypothesis within the framework of the black-box approaches provides only a bird’s-eye perspective on the long-run income-environment relationship. The aspiration behind this study is making the first step toward the disentanglement of the sources of carbon dioxide emissions, which could be employed in the pollution mitigation policies of this group of countries. Based on the combination of two strands of literature, the environmental Kuznets curve conjecture and the resource curse, the paper at hand proposes an augmented theoretical framework of this inquiry. To approach the research questions empirically, the study employs advanced panel cointegration techniques. To avoid econometric misspecification, the study also employs for the first time a nonparametric time-varying coefficient panel data estimator with fixed effects (NPFE) for the dataset of 37 oil-producing countries in the time interval spanning between 1989 and 2019. The empirical analysis identifies the level of per capita income, the magnitude of oil rents, the share of fossil fuel-based electricity generation in the energy mix, and the share of the manufacturing sector in GDP as essential drivers of carbon dioxide emissions in the oil-rich countries. Tertiarization, on the contrary, leads to a substantial reduction of emissions. Another striking result of this study is that level of political rights and civil liberties are negatively associated with per capita carbon emissions in this group of countries. Furthermore, the study decisively rejects an inverted U-shaped income-emission relationship and validates the monotonically or exponentially increasing impact of average income on carbon dioxide emissions.

Popularity Brings Better Sales or Vice Versa: Evidence from Instagram and OpenTable

2021 ◽  
pp. 097215092110443
Author(s):  
Hanane Lasmi ◽  
Chul Ho Lee ◽  
Yasin Ceran
Keyword(s):  
Granger Causality ◽  
Fixed Effects ◽  
Business Performance ◽  
Spillover Effect ◽  
Restaurant Industry ◽  
Reverse Causality ◽  
Positive Effects ◽  
Verse Effect ◽  
The Impact ◽  
Panel Vector Autoregression

With the popularity of user-generated content (UGC), an increasing number of studies have investigated its impact on business performance. However, prior studies were limited to a single platform and showed the effects of UGC of a platform, for example, customer textual comments or customer numeral ratings, on sales/reservation of the same platform. In practice, users often refer to a UGC, for example, Instagram, and purchase it on other platforms. To incorporate the spillover effect, we considered the restaurant industry because it has active participation across various channels. Using topic modelling, we first identified from Instagram four topics of users’ interest regarding a restaurant, such as location, nightlife, food and celebration. From fixed effects models’ estimation, we found that (a) recommendation and mention of Instagram have positive effects, and (b) comments of location and food also have positive significant fixed effects, but (c) the impact of Instagram volume is curvilinear and positive significant effect the sales. Since the curvilinear effects may come from reverse causality, that is, higher reservation, might bring more customers and comments on social networking service (SNS) (echo verse effect in our paper). Therefore, we further analysed two-way Granger causality and panel vector autoregression to identify the endogeneity, and the results showed the existing Granger causality loop between OpenTable review and Instagram post volumes.

Assessing the Impact of the Factors in the Digital Transformation on the Regional Economic Growth

REGIONOLOGY ◽  
2021 ◽  
Vol 29 (3) ◽  
pp. 486-510
Author(s):  
Tatyana V. Mirolyubova ◽  
Marina V. Radionova
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Fixed Effects ◽  
Digital Transformation ◽  
Regional Economic Growth ◽  
Regional Economic ◽  
The Russian Federation ◽  
Regional Product ◽  
The Impact ◽  
Regions Of Russia

Introduction. The scientific problem under consideration is of particular relevance due to the need to assess the impact of the factors in the digital transformation of the regional economy and in the economic growth on the economic development of the regions of the Russian Federation. Based on the research conducted, the article presents an econometric assessment of the dependence of the level of the gross regional product per capita in the regions of Russia on such factors as digital labor and digital capital. Materials and Methods. The authors analyzed panel data from the Federal State Statistics Service covering 87 regions of Russia for the period from 2010 to 2018. The research methodology is based on the use of the Cobb–Douglas production function, statistical and correlation data analysis, as well as on econometric methods for studying panel data. Results. To analyze the impact of the digital transformation of the economy on the regional economic growth of the regions of Russia, various models based on panel data have been considered, such as the pooled model, fixed effects models, random effects models, as well as time-varying effects models using dummy variables. Based on statistical criteria, the best model has been chosen and conclusions have been drawn about the nature of the impact of the digital transformation indicators on the gross regional product per capita in the regions of Russia. Discussion and Conclusion. The results of econometric modeling have demonstrated that digital factors in economic growth (digital labor, digital capital), along with common factors in economic growth (labor and capital), affect the regional economic growth. According to the regional data for the period from 2010 to 2018, the time fixed effects model has proved to be the best model of the impact of the factors in economic growth and digital transformation on the economic development of the regions of the Russian Federation. The research results can be used when developing a public policy aimed at stimulating the digital transformation of the regional economy.

scholarly journals Does the Credit Cycle Have an Impact on Happiness?

2019 ◽  
Vol 17 (1) ◽  
pp. 183 ◽  
Author(s):  
Tinghui Li ◽  
Junhao Zhong ◽  
Mark Xu
Keyword(s):  
Fixed Effects ◽  
Well Being ◽  
Gdp Per Capita ◽  
Subjective Well Being ◽  
Fixed Effects Model ◽  
Credit Expansion ◽  
Transmission Channels ◽  
Credit Cycle ◽  
Per Capita ◽  
The Relationship

The 2008 international financial crisis triggered a heated discussion of the relationship between public health and the economic environment. We test the relationship between the credit cycle and happiness using the fixed effects model and explore the transmission channels between them by adding the moderating effect. The results show the following empirical regularities. First, the credit cycle has a negative correlation with happiness. This means that credit growth will reduce the overall happiness score in a country/region. Second, the transmission channels between the credit cycle and happiness are different during credit expansion and recession. Life expectancy and generosity can moderate the relationship between the credit cycle and happiness only during credit expansion. GDP per capita can moderate this relationship only during credit recession. Social support, freedom, and positive affect can moderate this relationship throughout the credit cycle. Third, the total impact of the credit cycle on happiness will become positive by the changes in the moderating effects. In general, we can improve subjective well-being if one of the following five conditions holds: (1) with the adequate support from the family and society, (2) with enough freedom, (3) with social generosity, (4) with a positive and optimistic outlook, and (5) with a high level of GDP per capita.

scholarly journals Socioeconomic Factors Contributing to Antibiotic Resistance in China: A Panel Data Analysis

Antibiotics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 994
Author(s):  
Xuemei Zhen ◽  
Jingchunyu Chen ◽  
Xueshan Sun ◽  
Qiang Sun ◽  
Shasha Guo ◽  
...  
Keyword(s):  
Antibiotic Resistance ◽  
Socioeconomic Factors ◽  
Health Expenditure ◽  
Mainland China ◽  
Generation Cephalosporin ◽  
Gdp Per Capita ◽  
Third Generation ◽  
Physician Density ◽  
Per Capita ◽  
Economic Zones

The relationship between socioeconomic factors and antibiotic resistance (ABR) prevalence remains a knowledge gap in China. In this study, our aim was to examine the association between ABR prevalence and socioeconomic factors across 30 provinces in mainland China. We used two measures of level of ABR: the proportion of methicillin-resistant Staphylococcus aureus (MRSA), third-generation cephalosporin-resistant Escherichia coli (3GCREC), and third-generation cephalosporin-resistant Klebsiella pneumoniae (3GCRKP), and the aggregate resistance. The data of ABR prevalence, education, gross domestic product (GDP) per capita, out-of-pocket (OOP) health expenditure, physician density, hospital bed density, and public toilet density during 2014 and 2018 in 30 provinces in mainland China were included. We examined the association between ABR prevalence and potential contributing socioeconomic factors using panel data modeling. In addition, we explored this relationship in the eastern, central, and western economic zones. Our results indicated that GDP per capita was significantly positively correlated with ABR in mainland China and the eastern economic zone; however, significantly positive associations did not exist in the central and western economic zones. Surprisingly, both higher GDP per capita and higher OOP health expenditure were associated with a higher level of MRSA, but a lower level of 3GCREC; higher physician density was associated with a lower level of MRSA, but a higher level of 3GCREC. In addition, ABR prevalence presented a decline trend during 2014 and 2018. Our study highlights that intervention measures tackling the development and spread of ABR in mainland China must better recognize and address the importance of social and economic determinants.

scholarly journals SARS-COV-2 Vaccines: What Indicators are Associated with the Worldwide Distribution of the First Doses

2021 ◽  
Vol 58 ◽  
pp. 004695802110601
Author(s):  
Marcos Felipe Falcão Sobral ◽  
Brigitte Renata Bezerra de Oliveira ◽  
Ana Iza Gomes da Penha Sobral ◽  
Marcelo Luiz Monteiro Marinho ◽  
Gisleia Benini Duarte ◽  
...  
Keyword(s):  
Population Density ◽  
Life Expectancy ◽  
Human Development ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
The United States ◽  
Gdp Per Capita ◽  
Reproduction Rate ◽  
Worldwide Distribution ◽  
Per Capita

The present study aimed to identify the factors associated with the distribution of the first doses of the COVID-19 vaccine. In this study, we used 9 variables: human development index (HDI), gross domestic product (GDP per capita), Gini index, population density, extreme poverty, life expectancy, COVID cases, COVID deaths, and reproduction rate. The time period was until February 1, 2021. The variable of interest was the sum of the days after the vaccine arrived in the countries. Pearson’s correlation coefficients were calculated, and t-test was performed between the groups that received and did not receive the immunizer, and finally, a stepwise linear regression model was used. 58 (30.4%) of the 191 countries received the SARS-CoV-2 vaccine. The countries that received the most doses were the United States, China, the United Kingdom, and Israel. Vaccine access in days showed a positive Pearson correlation HDI, GDP, life expectancy, COVID-19 cases, deaths, and reproduction rate. Human development level, COVID-19 deaths, GDP per capita, and population density are able to explain almost 50% of the speed of access to immunizers. Countries with higher HDI and per capita income obtained priority access.

Sign in / Sign up

Export Citation Format

Share Document